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| Criterion |  Knowledge Modeling Knowledge Mapping |  Knowledge Modeling Shape-First Modeling |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 1-3 h | Halber Tag pro Domain Slice | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-12 | 1-4 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Knowledge Map, Critical Knowledge Areas, Transfer Plan | SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape Documentation | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | KnowledgeMappingRisk | Knowledge graphValidationSemantic | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |